Important Dates
Early Bird Registration :18th July 2026
Paper Submission Deadline :23rd July 2026
Last Date of Registration : 2nd August 2026
Date of Conference : 17th - 18th August 2026
Conference Session Tracks
Aligned with
UN Sustainable Development Goals
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.
SDG 3 — Good Health and Well-being
SDG 9 — Industry, Innovation and Infrastructure
SDG 10 — Reduced Inequalities
Track 01
Advancements in Image Segmentation Techniques
This track focuses on the latest methodologies in image segmentation within medical imaging. Researchers are invited to present novel algorithms and frameworks that enhance the accuracy and efficiency of segmentation processes.
Track 02
Machine Learning Approaches for Image Classification
This session explores innovative machine learning techniques for classifying medical images. Contributions should highlight advancements in supervised and unsupervised learning paradigms tailored for diagnostic purposes.
Track 03
Feature Extraction and Selection in Medical Imaging
This track emphasizes the importance of feature extraction and selection in enhancing machine learning models for medical imaging. Participants are encouraged to discuss new methods that improve the interpretability and performance of predictive models.
Track 04
Pattern Recognition in Radiological Data
This session delves into the application of pattern recognition techniques in analyzing radiological images. Papers should address challenges and solutions in detecting anomalies and patterns that aid in diagnosis.
Track 05
Predictive Modeling in Healthcare Analytics
This track focuses on the development of predictive models that leverage machine learning for healthcare analytics. Submissions should demonstrate the impact of these models on patient outcomes and clinical decision-making.
Track 06
Deep Learning Innovations in Imaging
This session highlights cutting-edge deep learning methodologies applied to medical imaging. Researchers are invited to present their findings on neural networks and their effectiveness in various imaging tasks.
Track 07
Anomaly Detection in Medical Imaging
This track addresses the critical area of anomaly detection in medical images using machine learning techniques. Contributions should focus on novel approaches that enhance the identification of rare or unusual patterns.
Track 08
Computer-Aided Diagnosis Systems
This session explores the integration of machine learning in computer-aided diagnosis systems. Papers should discuss the design, implementation, and evaluation of systems that assist radiologists in clinical settings.
Track 09
Neural Networks for Imaging Applications
This track focuses on the application of various neural network architectures in medical imaging tasks. Researchers are encouraged to share insights on model performance and real-world applications.
Track 10
Object Detection Techniques in Medical Imaging
This session investigates the latest advancements in object detection methodologies for medical imaging. Contributions should emphasize the challenges and solutions in accurately identifying anatomical structures and pathologies.
Track 11
Visual Analytics in Medical Imaging
This track emphasizes the role of visual analytics in interpreting complex medical imaging data. Participants are invited to present innovative tools and techniques that enhance data visualization and decision support.